diff --git a/pages/AI Risks___Ethical Concerns___Value Alignment Issues.md b/pages/AI Risks___Ethical Concerns___Value Alignment Issues.md new file mode 100644 index 0000000..88f9dcd --- /dev/null +++ b/pages/AI Risks___Ethical Concerns___Value Alignment Issues.md @@ -0,0 +1,2 @@ +- See [[Human Value Drift]] and [[AI Risks/Ethical Concerns/Bias]] +- \ No newline at end of file diff --git a/pages/AI Risks___Performance & Robustness___Performance Degradation.md b/pages/AI Risks___Performance & Robustness___Performance Degradation.md new file mode 100644 index 0000000..2d1b571 --- /dev/null +++ b/pages/AI Risks___Performance & Robustness___Performance Degradation.md @@ -0,0 +1 @@ +- See [[AI Risks/Performance & Robustness]] \ No newline at end of file diff --git a/pages/AI use cases.md b/pages/AI use cases.md new file mode 100644 index 0000000..5881e8e --- /dev/null +++ b/pages/AI use cases.md @@ -0,0 +1,763 @@ +## Financial Services Industry +- ### [[Use Cases/Financial Services/Investment Management]] + - {{embed [[Use Cases/Financial Services/Investment Management]]}} +- ### [[Use Cases/Financial Services/Retail Banking]] + - **[[Fraud Detection and Prevention]]** + collapsed:: true + - **Description**: Detects and prevents fraudulent activities in real-time using transaction data analysis. + - **Datasets**: + - [[Financial Services/Retail Banking/Transaction Data/Bank Transactions]] + - [[Financial Services/Retail Banking/Customer Data/Customer Profiles]] + - **Applicable Policies**: + - [[Policies/Data Governance/Fraud Detection]] + - [[Policies/Security/Incident Response]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Retail Banking/Fraud Detection and Prevention]] + - **[[Customer Churn Prediction]]** + collapsed:: true + - **Description**: Predicts the likelihood of customers leaving the bank by analyzing their transaction and interaction history. + - **Datasets**: + - [[Financial Services/Retail Banking/Customer Data/Customer Transactions]] + - [[Financial Services/Retail Banking/Customer Data/Customer Support Interactions]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Retail Banking/Customer Churn Prediction]] + - **[[Personalized Banking Recommendations]]** + collapsed:: true + - **Description**: Provides personalized financial products and services to customers based on their profile and behavior. + - **Datasets**: + - [[Financial Services/Retail Banking/Customer Data/Customer Profiles]] + - [[Financial Services/Retail Banking/Transaction Data/Customer Spending Patterns]] + - **Applicable Policies**: + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Retail Banking/Personalized Banking Recommendations]] + - **[[Loan Approval Automation]]** + collapsed:: true + - **Description**: Automates the loan approval process using predictive models that assess creditworthiness. + - **Datasets**: + - [[Financial Services/Retail Banking/Customer Data/Credit Scores]] + - [[Financial Services/Retail Banking/Financial Data/Income and Employment History]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Retail Banking/Loan Approval Automation]] +- ### [[Use Cases/Financial Services/Insurance]] + - **Claims Processing Automation** + collapsed:: true + - **Description**: Uses AI to process insurance claims automatically, reducing time and errors in claims management. + - **Datasets**: + - [[Financial Services/Insurance/Claims Data/Insurance Claims]] + - [[Financial Services/Insurance/Customer Data/Policyholder Information]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Classification]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Insurance/Claims Processing Automation]] + - **Risk Assessment and Pricing** + collapsed:: true + - **Description**: Uses predictive analytics to assess insurance risks and determine appropriate pricing for policies. + - **Datasets**: + - [[Financial Services/Insurance/Customer Data/Policyholder Risk Profiles]] + - [[Financial Services/Insurance/Claims Data/Historical Claims]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Access]] + - [[Policies/AI Governance/Risk Identification and Assessment]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Insurance/Risk Assessment and Pricing]] + - **Fraud Detection in Claims** + collapsed:: true + - **Description**: Detects fraudulent claims by analyzing historical claims data for patterns and anomalies. + - **Datasets**: + - [[Financial Services/Insurance/Claims Data/Historical Claims]] + - [[Financial Services/Insurance/Customer Data/Claimant Profiles]] + - **Applicable Policies**: + - [[Policies/Data Governance/Fraud Detection]] + - [[Policies/Security/Data Breach Response]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Insurance/Fraud Detection in Claims]] + - **Customer Support Automation** + collapsed:: true + - **Description**: Automates customer interactions using AI chatbots for insurance inquiries and policy management. + - **Datasets**: + - [[Financial Services/Insurance/Customer Data/Customer Interactions]] + - [[Financial Services/Insurance/Policy Data/Insurance Policies]] + - **Applicable Policies**: + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/Security/Identity and Access Management (IAM)]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Insurance/Customer Support Automation]] +- ### [[Use Cases/Financial Services/Wealth Management]] + - **Personalized Investment Recommendations** + collapsed:: true + - **Description**: Recommends investment strategies tailored to individual client goals and risk tolerance. + - **Datasets**: + - [[Financial Services/Wealth Management/Customer Data/Client Profiles]] + - [[Financial Services/Wealth Management/Market Data/Investment Opportunities]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Wealth Management/Personalized Investment Recommendations]] + - **Client Segmentation and Profiling** + collapsed:: true + - **Description**: Groups clients based on investment behavior and preferences to offer personalized services. + - **Datasets**: + - [[Financial Services/Wealth Management/Customer Data/Client Demographics]] + - [[Financial Services/Wealth Management/Transaction Data/Investment Patterns]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Classification]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Wealth Management/Client Segmentation and Profiling]] + - **Tax Optimization Strategies** + collapsed:: true + - **Description**: Uses financial data to provide clients with strategies to minimize tax liabilities. + - **Datasets**: + - [[Financial Services/Wealth Management/Financial Data/Tax Data]] + - [[Financial Services/Wealth Management/Transaction Data/Investment Transactions]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Wealth Management/Tax Optimization Strategies]] + - **Automated Portfolio Rebalancing** + collapsed:: true + - **Description**: Automatically adjusts client portfolios based on predefined rules and market conditions. + - **Datasets**: + - [[Financial Services/Wealth Management/Market Data/Asset Performance]] + - [[Financial Services/Wealth Management/Customer Data/Portfolio Holdings]] + - **Applicable Policies**: + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/AI Governance/Model Monitoring]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Wealth Management/Automated Portfolio Rebalancing]] +- ### [[Use Cases/Financial Services/Payments & Transactions]] +- **Fraud Detection in Transactions** + collapsed:: true + - **Description**: Real-time detection and prevention of fraudulent transactions using advanced analytics. + - **Datasets**: + - [[Financial Services/Payments & Transactions/Transaction Data/Transaction History]] + - [[Financial Services/Payments & Transactions/Customer Data/Customer Profiles]] + - **Applicable Policies**: + - [[Policies/Security/Fraud Detection]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Payments & Transactions/Fraud Detection in Transactions]] +- **Payment Gateway Optimization** + collapsed:: true + - **Description**: Optimizes the payment process to reduce failures and improve transaction speed. + - **Datasets**: + - [[Financial Services/Payments & Transactions/Transaction Data/Payment Gateway Logs]] + - [[Financial Services/Payments & Transactions/Transaction Data/Transaction History]] + - **Applicable Policies**: + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/Data Governance/Data Quality]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Payments & Transactions/Payment Gateway Optimization]] +- **Customer Behavior Analysis** + collapsed:: true + - **Description**: Analyzes customer transaction data to understand spending behavior and preferences. + - **Datasets**: + - [[Financial Services/Payments & Transactions/Transaction Data/Transaction History]] + - [[Financial Services/Payments & Transactions/Customer Data/Customer Profiles]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Payments & Transactions/Customer Behavior Analysis]] +- **Real-Time Transaction Monitoring** + collapsed:: true + - **Description**: Monitors transactions in real-time to detect anomalies and prevent fraudulent activities. + - **Datasets**: + - [[Financial Services/Payments & Transactions/Transaction Data/Real-Time Transactions]] + - [[Financial Services/Payments & Transactions/Transaction Data/Transaction History]] + - **Applicable Policies**: + - [[Policies/Security/Incident Response]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Financial Services/Payments & Transactions/Real-Time Transaction Monitoring]] +- # Healthcare Industry +- ### [[Use Cases/Healthcare/Hospitals and Healthcare Providers]] +- **Predictive Patient Diagnostics** + - **Description**: Predicts patient health outcomes using historical medical data to support early diagnosis and treatment. + - **Datasets**: + - [[Healthcare/Hospitals and Healthcare Providers/Patient Data/EHR]] + - [[Healthcare/Hospitals and Healthcare Providers/Patient Data/Lab Results]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Hospitals and Healthcare Providers/Predictive Patient Diagnostics]] +- **Medical Image Analysis** + - **Description**: Uses computer vision to analyze medical images for disease detection and diagnosis. + - **Datasets**: + - [[Healthcare/Hospitals and Healthcare Providers/Image Data/MRI Scans]] + - [[Healthcare/Hospitals and Healthcare Providers/Image Data/X-Ray Images]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Hospitals and Healthcare Providers/Medical Image Analysis]] +- **Electronic Health Record (EHR) Management** + - **Description**: Organizes and standardizes patient data to improve accessibility and quality of care. + - **Datasets**: + - [[Healthcare/Hospitals and Healthcare Providers/Patient Data/EHR]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Hospitals and Healthcare Providers/EHR Management]] +- **Patient Risk Scoring** + - **Description**: Scores patient risk levels for developing certain conditions based on health records. + - **Datasets**: + - [[Healthcare/Hospitals and Healthcare Providers/Patient Data/EHR]] + - [[Healthcare/Hospitals and Healthcare Providers/Patient Data/Demographics]] + - **Applicable Policies**: + - [[Policies/AI Governance/Model Validation]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Hospitals and Healthcare Providers/Patient Risk Scoring]] +- ### [[Use Cases/Healthcare/Pharmaceuticals]] +- **Drug Discovery and Development** + - **Description**: Accelerates the process of drug discovery using AI to identify potential compounds and predict their effectiveness. + - **Datasets**: + - [[Healthcare/Pharmaceuticals/Research Data/Chemical Properties]] + - [[Healthcare/Pharmaceuticals/Research Data/Genomic Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Pharmaceuticals/Drug Discovery and Development]] +- **Clinical Trial Optimization** + - **Description**: Optimizes the selection of participants and design of clinical trials to increase their efficiency and success rate. + - **Datasets**: + - [[Healthcare/Pharmaceuticals/Clinical Data/Trial Participants]] + - [[Healthcare/Pharmaceuticals/Clinical Data/Study Results]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Pharmaceuticals/Clinical Trial Optimization]] +- **Adverse Event Detection** + - **Description**: Predicts and identifies adverse drug reactions using patient data. + - **Datasets**: + - [[Healthcare/Pharmaceuticals/Clinical Data/Patient Reports]] + - [[Healthcare/Pharmaceuticals/Clinical Data/Drug Usage]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Model Monitoring]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Pharmaceuticals/Adverse Event Detection]] +- **Supply Chain Management for Drugs** + - **Description**: Optimizes the pharmaceutical supply chain to ensure timely delivery and minimize wastage. + - **Datasets**: + - [[Healthcare/Pharmaceuticals/Supply Chain Data/Inventory Levels]] + - [[Healthcare/Pharmaceuticals/Logistics Data/Distribution Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Operational Data Retention]] + - [[Policies/AI Governance/Risk Management]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Healthcare/Pharmaceuticals/Supply Chain Management for Drugs]] +- # Retail & E-commerce Industry +- ### [[Use Cases/Retail/Brick-and-Mortar Retail]] +- **Demand Forecasting and Inventory Management** + - **Description**: Predicts product demand to optimize inventory levels and reduce overstocking or stockouts. + - **Datasets**: + - [[Retail/Brick-and-Mortar Retail/Sales Data/Past Sales]] + - [[Retail/Brick-and-Mortar Retail/Inventory Data/Stock Levels]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Brick-and-Mortar Retail/Demand Forecasting and Inventory Management]] +- **Store Layout Optimization** + - **Description**: Uses data to design store layouts that maximize customer engagement and sales. + - **Datasets**: + - [[Retail/Brick-and-Mortar Retail/Customer Data/Foot Traffic Patterns]] + - [[Retail/Brick-and-Mortar Retail/Sales Data/Product Sales]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Brick-and-Mortar Retail/Store Layout Optimization]] +- **Customer Sentiment Analysis** + - **Description**: Analyzes customer feedback from multiple channels to gauge sentiment and improve service. + - **Datasets**: + - [[Retail/Brick-and-Mortar Retail/Customer Feedback/Reviews and Ratings]] + - [[Retail/Brick-and-Mortar Retail/Social Media Data/Mentions and Comments]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Brick-and-Mortar Retail/Customer Sentiment Analysis]] +- **Loyalty Program Personalization** + - **Description**: Tailors loyalty rewards based on individual customer behavior and preferences. + - **Datasets**: + - [[Retail/Brick-and-Mortar Retail/Customer Data/Loyalty Program Participation]] + - [[Retail/Brick-and-Mortar Retail/Transaction Data/Purchase History]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Brick-and-Mortar Retail/Loyalty Program Personalization]] +- ### [[Use Cases/Retail/Online Retail & Marketplaces]] +- **Personalized Product Recommendations** + - **Description**: Suggests products to customers based on their browsing history and past purchases. + - **Datasets**: + - [[Retail/Online Retail & Marketplaces/Customer Data/Browsing History]] + - [[Retail/Online Retail & Marketplaces/Transaction Data/Purchase History]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Online Retail & Marketplaces/Personalized Product Recommendations]] +- **Chatbots for Customer Support** + - **Description**: Provides automated responses to common customer inquiries, improving response time and efficiency. + - **Datasets**: + - [[Retail/Online Retail & Marketplaces/Customer Data/Support Interactions]] + - [[Retail/Online Retail & Marketplaces/FAQ Data/Support Topics]] + - **Applicable Policies**: + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/Security/Identity and Access Management (IAM)]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Online Retail & Marketplaces/Chatbots for Customer Support]] +- **Supply Chain and Logistics Optimization** + - **Description**: Uses predictive analytics to optimize the supply chain, ensuring efficient product delivery. + - **Datasets**: + - [[Retail/Online Retail & Marketplaces/Logistics Data/Shipment Tracking]] + - [[Retail/Online Retail & Marketplaces/Supply Chain Data/Warehouse Inventory]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Monitoring]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Online Retail & Marketplaces/Supply Chain and Logistics Optimization]] +- **Fraud Detection in Transactions** + - **Description**: Identifies suspicious activities in online transactions to prevent fraud. + - **Datasets**: + - [[Retail/Online Retail & Marketplaces/Transaction Data/Payment Transactions]] + - [[Retail/Online Retail & Marketplaces/Customer Data/User Profiles]] + - **Applicable Policies**: + - [[Policies/Security/Fraud Detection]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Retail/Online Retail & Marketplaces/Fraud Detection in Transactions]] +- # Manufacturing Industry +- ### [[Use Cases/Manufacturing/Discrete Manufacturing]] +- **Predictive Maintenance** + - **Description**: Predicts equipment failures before they occur, minimizing downtime and repair costs. + - **Datasets**: + - [[Manufacturing/Discrete Manufacturing/Equipment Data/Sensor Readings]] + - [[Manufacturing/Discrete Manufacturing/Maintenance Data/Service Records]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Discrete Manufacturing/Predictive Maintenance]] +- **Quality Control and Defect Detection** + - **Description**: Uses AI to detect defects in products during the manufacturing process. + - **Datasets**: + - [[Manufacturing/Discrete Manufacturing/Image Data/Product Images]] + - [[Manufacturing/Discrete Manufacturing/Production Data/Quality Metrics]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Discrete Manufacturing/Quality Control and Defect Detection]] +- **Supply Chain Optimization** + - **Description**: Optimizes supply chain operations to reduce costs and improve delivery times. + - **Datasets**: + - [[Manufacturing/Discrete Manufacturing/Supply Chain Data/Logistics]] + - [[Manufacturing/Discrete Manufacturing/Inventory Data/Stock Levels]] + - **Applicable Policies**: + - [[Policies/Data Governance/Operational Data Retention]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Discrete Manufacturing/Supply Chain Optimization]] +- **Production Planning and Scheduling** + - **Description**: Plans and schedules production runs to meet demand while minimizing costs and maximizing efficiency. + - **Datasets**: + - [[Manufacturing/Discrete Manufacturing/Production Data/Production Schedules]] + - [[Manufacturing/Discrete Manufacturing/Demand Data/Forecasts]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Monitoring]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Discrete Manufacturing/Production Planning and Scheduling]] +- ### [[Use Cases/Manufacturing/Process Manufacturing]] +- **Process Optimization and Control** + - **Description**: Uses data analytics to optimize manufacturing processes and control production quality. + - **Datasets**: + - [[Manufacturing/Process Manufacturing/Process Data/Operational Data]] + - [[Manufacturing/Process Manufacturing/Product Data/Quality Metrics]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Process Manufacturing/Process Optimization and Control]] +- **Yield Optimization** + - **Description**: Optimizes production processes to maximize yield and minimize waste. + - **Datasets**: + - [[Manufacturing/Process Manufacturing/Production Data/Yield Data]] + - [[Manufacturing/Process Manufacturing/Resource Data/Raw Material Usage]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Process Manufacturing/Yield Optimization]] +- **Predictive Maintenance for Equipment** + - **Description**: Predicts when equipment will fail so that maintenance can be performed just in time to avoid downtime. + - **Datasets**: + - [[Manufacturing/Process Manufacturing/Equipment Data/Sensor Readings]] + - [[Manufacturing/Process Manufacturing/Maintenance Data/Service Records]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Process Manufacturing/Predictive Maintenance for Equipment]] +- **Energy Consumption Optimization** + - **Description**: Optimizes energy usage during the manufacturing process to reduce costs and environmental impact. + - **Datasets**: + - [[Manufacturing/Process Manufacturing/Energy Data/Consumption Metrics]] + - [[Manufacturing/Process Manufacturing/Production Data/Process Efficiency]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Manufacturing/Process Manufacturing/Energy Consumption Optimization]] +- # Energy & Utilities Industry +- ### [[Use Cases/Energy/Electric Utilities]] +- **Smart Grid Management** + - **Description**: Manages the distribution of electricity more efficiently using real-time data from the grid. + - **Datasets**: + - [[Energy/Electric Utilities/Grid Data/Smart Meter Data]] + - [[Energy/Electric Utilities/Load Data/Consumption Patterns]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Risk Management]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Electric Utilities/Smart Grid Management]] +- **Predictive Maintenance for Equipment** + - **Description**: Predicts when utility equipment will fail so that maintenance can be scheduled proactively. + - **Datasets**: + - [[Energy/Electric Utilities/Equipment Data/Sensor Readings]] + - [[Energy/Electric Utilities/Maintenance Data/Service Records]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Electric Utilities/Predictive Maintenance for Equipment]] +- **Energy Demand Forecasting** + - **Description**: Predicts future energy demand to help utilities plan for production and distribution. + - **Datasets**: + - [[Energy/Electric Utilities/Demand Data/Historical Demand]] + - [[Energy/Electric Utilities/Weather Data/Weather Forecasts]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Monitoring]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Electric Utilities/Energy Demand Forecasting]] +- **Renewable Energy Integration** + - **Description**: Integrates renewable energy sources into the power grid while maintaining grid stability. + - **Datasets**: + - [[Energy/Electric Utilities/Renewable Energy Data/Generation Data]] + - [[Energy/Electric Utilities/Grid Data/Grid Stability Metrics]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Risk Management]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Electric Utilities/Renewable Energy Integration]] +- ### [[Use Cases/Energy/Oil & Gas]] +- **Predictive Maintenance for Equipment** + - **Description**: Uses data from sensors and historical maintenance records to predict when equipment is likely to fail. + - **Datasets**: + - [[Energy/Oil & Gas/Equipment Data/Sensor Data]] + - [[Energy/Oil & Gas/Maintenance Data/Service History]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Oil & Gas/Predictive Maintenance for Equipment]] +- **Reservoir Optimization** + - **Description**: Optimizes oil and gas reservoir management to maximize extraction efficiency and reduce costs. + - **Datasets**: + - [[Energy/Oil & Gas/Geological Data/Reservoir Characteristics]] + - [[Energy/Oil & Gas/Production Data/Extraction Rates]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Oil & Gas/Reservoir Optimization]] +- **Supply Chain and Logistics Optimization** + - **Description**: Uses predictive analytics to optimize the supply chain for oil and gas distribution. + - **Datasets**: + - [[Energy/Oil & Gas/Logistics Data/Shipment Data]] + - [[Energy/Oil & Gas/Supply Chain Data/Inventory Levels]] + - **Applicable Policies**: + - [[Policies/Data Governance/Operational Data Retention]] + - [[Policies/AI Governance/Risk Management]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Oil & Gas/Supply Chain and Logistics Optimization]] +- **Energy Consumption Optimization** + - **Description**: Analyzes energy consumption data to find ways to reduce usage and improve efficiency. + - **Datasets**: + - [[Energy/Oil & Gas/Energy Data/Consumption Data]] + - [[Energy/Oil & Gas/Production Data/Efficiency Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Energy/Oil & Gas/Energy Consumption Optimization]] +- # Transportation & Logistics Industry +- ### [[Use Cases/Transportation/Freight & Logistics]] +- **Route Optimization** + - **Description**: Optimizes delivery routes to reduce fuel consumption and delivery times. + - **Datasets**: + - [[Transportation/Freight & Logistics/Route Data/Delivery Routes]] + - [[Transportation/Freight & Logistics/Traffic Data/Traffic Conditions]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Freight & Logistics/Route Optimization]] +- **Predictive Maintenance for Vehicles** + - **Description**: Predicts when fleet vehicles will need maintenance to avoid unexpected breakdowns. + - **Datasets**: + - [[Transportation/Freight & Logistics/Vehicle Data/Sensor Readings]] + - [[Transportation/Freight & Logistics/Maintenance Data/Service Records]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Freight & Logistics/Predictive Maintenance for Vehicles]] +- **Supply Chain and Inventory Optimization** + - **Description**: Optimizes the supply chain and inventory management to reduce costs and improve efficiency. + - **Datasets**: + - [[Transportation/Freight & Logistics/Supply Chain Data/Inventory Levels]] + - [[Transportation/Freight & Logistics/Logistics Data/Shipment Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Monitoring]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Freight & Logistics/Supply Chain and Inventory Optimization]] +- **Fleet Management and Optimization** + - **Description**: Manages the fleet of vehicles to improve efficiency and reduce operational costs. + - **Datasets**: + - [[Transportation/Freight & Logistics/Fleet Data/Vehicle Usage]] + - [[Transportation/Freight & Logistics/Logistics Data/Shipment Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Freight & Logistics/Fleet Management and Optimization]] +- ### [[Use Cases/Transportation/Public Transportation]] +- **Passenger Flow Prediction** + - **Description**: Predicts passenger flow to optimize scheduling and reduce congestion. + - **Datasets**: + - [[Transportation/Public Transportation/Passenger Data/Historical Passenger Counts]] + - [[Transportation/Public Transportation/Route Data/Route Usage]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Public Transportation/Passenger Flow Prediction]] +- **Route Optimization and Planning** + - **Description**: Uses data to plan and optimize public transportation routes for efficiency. + - **Datasets**: + - [[Transportation/Public Transportation/Route Data/Current Routes]] + - [[Transportation/Public Transportation/Traffic Data/Traffic Conditions]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Public Transportation/Route Optimization and Planning]] +- **Predictive Maintenance for Infrastructure** + - **Description**: Predicts when public transportation infrastructure will need maintenance to avoid failures. + - **Datasets**: + - [[Transportation/Public Transportation/Infrastructure Data/Sensor Readings]] + - [[Transportation/Public Transportation/Maintenance Data/Service Records]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Public Transportation/Predictive Maintenance for Infrastructure]] +- **Fare Evasion Detection** + - **Description**: Detects fare evasion using data from ticketing systems and surveillance cameras. + - **Datasets**: + - [[Transportation/Public Transportation/Ticketing Data/Fare Data]] + - [[Transportation/Public Transportation/Surveillance Data/CCTV Footage]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Transportation/Public Transportation/Fare Evasion Detection]] +- # Telecommunications Industry +- ### [[Use Cases/Telecommunications/Network Providers]] +- **Network Optimization and Management** + - **Description**: Uses data analytics to optimize network performance and manage resources efficiently. + - **Datasets**: + - [[Telecommunications/Network Providers/Network Data/Usage Statistics]] + - [[Telecommunications/Network Providers/Equipment Data/Performance Metrics]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/Network Providers/Network Optimization and Management]] +- **Predictive Maintenance for Network Equipment** + - **Description**: Predicts when network equipment will fail to minimize outages and service disruptions. + - **Datasets**: + - [[Telecommunications/Network Providers/Equipment Data/Sensor Readings]] + - [[Telecommunications/Network Providers/Maintenance Data/Service Records]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/AI Governance/Model Validation]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/Network Providers/Predictive Maintenance for Network Equipment]] +- **Customer Churn Prediction** + - **Description**: Predicts which customers are likely to leave the service to enable proactive retention efforts. + - **Datasets**: + - [[Telecommunications/Network Providers/Customer Data/Service Usage]] + - [[Telecommunications/Network Providers/Customer Data/Support Interactions]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/Network Providers/Customer Churn Prediction]] +- **Fraud Detection** + - **Description**: Detects fraudulent activities such as unauthorized access or billing anomalies in the network. + - **Datasets**: + - [[Telecommunications/Network Providers/Network Data/Usage Data]] + - [[Telecommunications/Network Providers/Customer Data/Billing Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Fraud Detection]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/Network Providers/Fraud Detection]] +- ### [[Use Cases/Telecommunications/Internet Service Providers (ISPs)]] +- **Bandwidth Optimization** + - **Description**: Analyzes network usage data to optimize bandwidth allocation and prevent congestion. + - **Datasets**: + - [[Telecommunications/ISPs/Network Data/Bandwidth Usage]] + - [[Telecommunications/ISPs/Customer Data/Service Usage]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Quality]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/ISPs/Bandwidth Optimization]] +- **Customer Support Automation** + - **Description**: Uses chatbots and virtual assistants to handle common customer support inquiries. + - **Datasets**: + - [[Telecommunications/ISPs/Customer Data/Support Interactions]] + - [[Telecommunications/ISPs/FAQ Data/Common Issues]] + - **Applicable Policies**: + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/Security/Identity and Access Management (IAM)]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/ISPs/Customer Support Automation]] +- **Predictive Customer Behavior Analysis** + - **Description**: Predicts customer behavior, such as data usage patterns, to offer personalized services. + - **Datasets**: + - [[Telecommunications/ISPs/Customer Data/Service Usage]] + - [[Telecommunications/ISPs/Customer Data/Support Interactions]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/ISPs/Predictive Customer Behavior Analysis]] +- **Fraud Detection and Prevention** + - **Description**: Identifies and prevents fraudulent activities such as identity theft or unauthorized access to services. + - **Datasets**: + - [[Telecommunications/ISPs/Network Data/Usage Data]] + - [[Telecommunications/ISPs/Customer Data/Billing Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Fraud Detection]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Telecommunications/ISPs/Fraud Detection and Prevention]] +- # Public Sector & Government Industry +- ### [[Use Cases/Public Sector/Law Enforcement & Public Safety]] +- **Predictive Policing** + - **Description**: Uses historical crime data to predict where crimes are likely to occur and allocate resources accordingly. + - **Datasets**: + - [[Public Sector/Law Enforcement/Crime Data/Incident Reports]] + - [[Public Sector/Law Enforcement/Demographic Data/Population Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Law Enforcement & Public Safety/Predictive Policing]] +- **Crime Pattern Analysis** + - **Description**: Analyzes crime data to identify patterns and trends that can inform law enforcement strategies. + - **Datasets**: + - [[Public Sector/Law Enforcement/Crime Data/Incident Reports]] + - [[Public Sector/Law Enforcement/Crime Data/Arrest Records]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Bias Detection Policy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Law Enforcement & Public Safety/Crime Pattern Analysis]] +- **Fraud Detection in Welfare Programs** + - **Description**: Detects fraudulent claims and activities within government welfare programs. + - **Datasets**: + - [[Public Sector/Welfare Programs/Claims Data/Welfare Claims]] + - [[Public Sector/Welfare Programs/Beneficiary Data/Eligibility Information]] + - **Applicable Policies**: + - [[Policies/Data Governance/Fraud Detection]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Law Enforcement & Public Safety/Fraud Detection in Welfare Programs]] +- **Public Health Monitoring** + - **Description**: Monitors public health data to detect early signs of outbreaks and inform public health interventions. + - **Datasets**: + - [[Public Sector/Public Health/Health Data/Outbreak Reports]] + - [[Public Sector/Public Health/Demographic Data/Population Health Data]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Law Enforcement & Public Safety/Public Health Monitoring]] +- ### [[Use Cases/Public Sector/Public Administration]] +- **Tax Fraud Detection** + - **Description**: Uses data analytics to detect fraudulent activities in tax filings and payments. + - **Datasets**: + - [[Public Sector/Taxation/Tax Data/Income Reports]] + - [[Public Sector/Taxation/Transaction Data/Financial Transactions]] + - **Applicable Policies**: + - [[Policies/Data Governance/Fraud Detection]] + - [[Policies/Data Governance/Data Privacy]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Public Administration/Tax Fraud Detection]] +- **Citizen Support Automation** + - **Description**: Automates responses to citizen inquiries and provides information on government services using AI chatbots. + - **Datasets**: + - [[Public Sector/Public Administration/Citizen Data/Support Inquiries]] + - [[Public Sector/Public Administration/Service Data/Government Services]] + - **Applicable Policies**: + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/Security/Identity and Access Management (IAM)]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Public Administration/Citizen Support Automation]] +- **Smart City Infrastructure Management** + - **Description**: Uses data analytics to optimize city infrastructure operations, such as traffic lights and public transportation. + - **Datasets**: + - [[Public Sector/Smart City/Infrastructure Data/Traffic Data]] + - [[Public Sector/Smart City/Utility Data/Water and Energy Usage]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Public Administration/Smart City Infrastructure Management]] +- **Natural Disaster Prediction and Response** + - **Description**: Predicts natural disasters and coordinates response efforts using real-time data. + - **Datasets**: + - [[Public Sector/Natural Disasters/Environmental Data/Weather Data]] + - [[Public Sector/Natural Disasters/Response Data/Emergency Response]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/AI Governance/Risk Management]] + - **MIT AI Risk Database**: + - [[MIT AI Risk/Public Sector/Public Administration/Natural Disaster Prediction and Response]] \ No newline at end of file diff --git a/pages/Credit Risk Assessment.md b/pages/Credit Risk Assessment.md new file mode 100644 index 0000000..ec5c967 --- /dev/null +++ b/pages/Credit Risk Assessment.md @@ -0,0 +1 @@ +alias:: Credit Risk Scoring diff --git a/pages/Credit Risk Scoring.md b/pages/Credit Risk Scoring.md new file mode 100644 index 0000000..e69de29 diff --git a/pages/Liability-Driven Investment (LDI) Strategy.md b/pages/Liability-Driven Investment (LDI) Strategy.md new file mode 100644 index 0000000..11486a2 --- /dev/null +++ b/pages/Liability-Driven Investment (LDI) Strategy.md @@ -0,0 +1 @@ +- See [[Liability-Driven Investment]], acronym: [[LDI]] \ No newline at end of file diff --git a/pages/Liability-Driven Investment.md b/pages/Liability-Driven Investment.md new file mode 100644 index 0000000..d200687 --- /dev/null +++ b/pages/Liability-Driven Investment.md @@ -0,0 +1 @@ +alias:: LDI diff --git a/pages/Portfolio Optimisation.md b/pages/Portfolio Optimisation.md new file mode 100644 index 0000000..b9394ed --- /dev/null +++ b/pages/Portfolio Optimisation.md @@ -0,0 +1 @@ +alias:: Asset Allocation Optimisation diff --git a/pages/Use Cases___Financial Services___Investment Management.md b/pages/Use Cases___Financial Services___Investment Management.md new file mode 100644 index 0000000..0701704 --- /dev/null +++ b/pages/Use Cases___Financial Services___Investment Management.md @@ -0,0 +1,731 @@ +### [[Portfolio Optimisation]] +collapsed:: true + - **Description**: Optimizes asset allocation for portfolios by balancing risk and return based on [[market data]]. + - AI Use Case: Optimize asset allocation based on risk-return profiles. + - Data Use Case: Historical market data analysis to identify trends. + - **Datasets**: + collapsed:: true + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Real-Time Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Real-Time Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Indices/Benchmark Index Data]] + - [[Financial Services/Investment Management/Client Data/Investor Profiles/Risk Tolerance]] + - [[Financial Services/Investment Management/Client Data/Investor Portfolios/Current Holdings]] + - [[Financial Services/Investment Management/Client Data/Fund Beneficiaries/Demographics]] + - [[Financial Services/Investment Management/Client Data/Fund Beneficiaries/Contribution History]] + - [[Financial Services/Investment Management/Client Data/Fund Liabilities/Projected Liabilities]] + - [[Financial Services/Investment Management/Economic Data/Inflation Rates]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - **AI Risks**: + - [[AI Risks/Untruthful Content/Factuality Errors]] + - [[AI Risks/Technology concerns/Explainability]] + - [[AI Risks/Model-level risk/Model bias]] + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[AI Risks/Performance & Robustness/Performance Degradation]] + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - [[...]] +- ### [[Algorithmic Trading]] + collapsed:: true + - **Description**: Uses real-time market data and predefined strategies to execute trades automatically. + - AI Use Case: Use machine learning algorithms to execute trades based on market conditions. + - Data Use Case: Backtesting trading strategies using historical data. + - **Datasets**: + collapsed:: true + - [[Financial Services/Investment Management/Market Data/Asset Prices/Real-Time Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Real-Time Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Trading Data/Historical Trade Data]] + - [[Financial Services/Investment Management/Market Data/Trading Data/Order Book Data]] + - [[Financial Services/Investment Management/Market Data/Trading Data/Execution Data]] + - [[Financial Services/Investment Management/Market Data/Indices/Real-Time Benchmark Index Data]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - **AI Risks**: + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Errors due to incorrect or outdated financial data affecting model outputs. + - [[AI Risks/Transparency - Explainability/Black-box Models]] + - [[AI Risks/Fairness & Bias/Market Manipulation]] + - [[AI Risks/Model-level risk/Model bias]] + - Bias in asset allocation models, leading to unfair advantages or disadvantages for certain assets or sectors. + - See [[Bias Detection]] + - [[AI Risks/Anthropomorphism/Degradation]] + - [[AI Risks/Performance & Robustness/Performance Degradation]] + - [[AI Risks/Accountability/Accountability]] + - [[AI Risks/Transparency - Explainability/Transparency - Explainability]] + collapsed:: true + - Difficulty in explaining the reasoning behind asset allocation decisions made by complex models. + - [[AI Risks/Ethical AI Risks /Misinterpretation of human value definitions/ ethics by AI systems]] + collapsed:: true + - Misalignment between the model’s optimization goals and the client’s ethical or [[ESG]] considerations. + - See also [[Human Value Drift]] + - [[...]] +- ### [[Risk Assessment and Mitigation]] + collapsed:: true + - AI Use Case: Predict potential risks and recommend mitigation strategies. + - Data Use Case: Analyze historical financial data to assess risk factors. + - **Description**: Predicts potential financial risks and recommends mitigation strategies using historical and real-time data. + - **Datasets**: + collapsed:: true + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Indices/Historical Benchmark Index Data]] + - [[Financial Services/Investment Management/Market Data/Economic Data/Macroeconomic Indicators]] + - [[Financial Services/Investment Management/Market Data/Economic Data/Country Risk Ratings]] + - [[Financial Services/Investment Management/Client Data/Investor Portfolios/Current Holdings]] + - [[Financial Services/Investment Management/Client Data/Investor Portfolios/Transaction History]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + collapsed:: true + - [[AI Risks/Bias and fairness/Bias and fairness]] in [[Credit Scoring]] and [[Risk Assessment]] + - [[AI Risks/Explainability & Transparency]] + - [[AI Risks/Untruthful Content/Factuality Errors]] + - [[AI Risks/Technology concerns/Explainability]] + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[Data Management/Risks/Data Integrity]] + - [[Data Management/Risks/Data Breach]] + - [[Data Management/Risks/Data Leakage]] +- ### [[Client Portfolio Reporting]] + collapsed:: true + - Data Use Case: Generate automated reports for client portfolios using financial data. + - **Description**: Automates the generation of client portfolio performance reports with visualizations and analytics. + - **Datasets**: + - [[Financial Services/Investment Management/Client Data/Investor Portfolios/Current Holdings]] + - [[Financial Services/Investment Management/Market Data/Indices/Benchmark Index Data]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Trading Data/Transaction Data]] + - [[Financial Services/Investment Management/Client Data/Investor Profiles/Risk Tolerance]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Inaccuracies in automated reports due to incorrect data feeds or misinterpretation of portfolio performance data. + - [[AI Risks/Technology concerns/Explainability]] + - Lack of clarity in automated reports on the rationale behind portfolio changes or recommendations. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - Reports that fail to reflect the client’s specific ESG considerations or ethical preferences. + - [[AI Risks/Privacy and Data Leakage]] + - [[AI Risks/Security/Security]] + - Unauthorized access to client portfolio data or reporting mechanisms. +- ### [[Market Sentiment Analysis]] + collapsed:: true + - AI Use Case: Analyze social media and news data to gauge market sentiment. + - Data Use Case: Text analysis of market-related news and social media posts. + - **Description**: Analyzes social media, news, and other textual data to gauge market sentiment and inform investment decisions. + - **Datasets**: + - [[Financial Services/Investment Management/Market Data/News Data/Financial News]] + - [[Financial Services/Investment Management/Market Data/Social Media Data/Market Sentiment]] + - [[Financial Services/Investment Management/Market Data/Indices/Benchmark Index Data]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Real-Time Stock Prices]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Misinterpretation of sentiment due to noisy or irrelevant data sources. + - [[AI Risks/Data-level risk/Data bias]] + - Bias in sentiment analysis algorithms due to unrepresentative training data. + - [[AI Risks/Bias and fairness/Bias and fairness]] + - [[AI Risks/Technology concerns/Explainability]] + - Challenges in explaining how sentiment analysis models derive their predictions. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - Misalignment between model outputs and the organization’s ethical guidelines or public relations stance. + - [[Data Management/Risks/Data Integrity]] + - Manipulation of input data sources, such as social media posts, to influence sentiment analysis. + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - Unauthorized access to proprietary sentiment analysis models or data sources. +- ### [[ESG Compliance Scoring]] + collapsed:: true + - AI Use Case: Automate scoring based on environmental, social, and governance data. + - Data Use Case: Collect and standardize ESG data for scoring. + - **Description**: Automates the evaluation and scoring of companies based on their environmental, social, and governance (ESG) performance. + - **Datasets**: + - [[Financial Services/Investment Management/Market Data/ESG Data/Company ESG Scores]] + - [[Financial Services/Investment Management/Market Data/News Data/ESG Related News]] + - [[Financial Services/Investment Management/Client Data/Investor Profiles/ESG Preferences]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Data-level risk/Data bias]] + - Bias in ESG scoring models due to incomplete or unbalanced ESG data. + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Inaccurate ESG scores due to incorrect data or misclassification. + - [[AI Risks/Technology concerns/Explainability]] + - Lack of transparency in how ESG scores are derived. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - Scores that do not align with the organization’s ESG principles or stakeholder + - [[Data Management/Risks/Data Integrity]] + - Risks related to tampering or falsification of ESG data inputs. + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[Data Management/Risks/Data Leakage]] + - Breach of proprietary ESG scoring methodologies or sensitive ESG data. +- ### [[Financial Forecasting]] + collapsed:: true + - AI Use Case: Predict future financial performance using time-series analysis. + - Data Use Case: Analyze historical financial statements for trend analysis. + - **Description**: Predicts future financial performance using historical data and statistical models. + - **Datasets**: + - [[Financial Services/Investment Management/Market Data/Financial Statements/Historical Financial Statements]] + - [[Financial Services/Investment Management/Market Data/Economic Data/Macroeconomic Indicators]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Indices/Historical Benchmark Index Data]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Model-level risk/Model bias]] + - [[Bias]] in forecasting models that disproportionately affect certain [[asset classes]] or [[sectors]]. + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Errors in forecasting due to incorrect or outdated [[financial data]]. + - [[AI Risks/Technology concerns/Explainability]] + - Difficulty in explaining complex time-series models and their predictions. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - Predictions that conflict with the organization’s stated values or ethical guidelines. + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[Data Management/Risks/Data Leakage]] + - Exposure of sensitive financial data or proprietary forecasting models. +- ### [[Credit Risk Assessment]] + collapsed:: true + - AI Use Case: Use machine learning to predict credit risk based on borrower data. + - Data Use Case: Historical credit data analysis to identify risk factors. + - **Description**: Uses predictive models to assess the credit risk of potential borrowers based on their financial data. + - **Datasets**: + - [[Financial Services/Investment Management/Client Data/Borrower Profiles/Credit History]] + - [[Financial Services/Investment Management/Client Data/Borrower Profiles/Income and Employment History]] + - [[Financial Services/Investment Management/Market Data/Economic Data/Credit Risk Indicators]] + - [[Financial Services/Investment Management/Market Data/Financial Statements/Company Financials]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Incorrect credit risk predictions due to flawed or incomplete data. + - [[AI Risks/Bias and fairness/Bias in Credit Scoring]] + - Bias in credit risk models that disproportionately affect certain demographics. + - [[AI Risks/Bias]] in [[Credit Risk Scoring]] + - [[AI Risks/Technology concerns/Explainability]] + - Challenges in explaining credit risk scores and model decisions. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - Credit risk assessments that conflict with the organization’s ethical principles or public commitments. + - [[Data Management/Risks/Data Integrity]] + - Manipulation or corruption of credit data used for risk assessments. + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[Data Management/Risks/Data Leakage]] + - Breach of sensitive borrower data or credit scoring models. +- ### [[Liability-Driven Investment (LDI) Strategy]] + collapsed:: true + - **Description**: Manages the Investment's assets in a way that matches its liabilities, ensuring the fund can meet its future obligations. + - **Datasets**: + - [[Financial Services/Investment Management/Client Data/Fund Liabilities/Projected Liabilities]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Real-Time Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Indices/Bond Index Data]] + - [[Financial Services/Investment Management/Economic Data/Interest Rates]] + - [[Financial Services/Investment Management/Economic Data/Inflation Rates]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Systemic/Systemic]] + - Model failures leading to an inability to meet long-term liabilities. + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Errors in matching assets to liabilities due to inaccurate projections or data. + - [[AI Risks/Bias and fairness]] + - [[AI Risks/Data-level risk/Data bias]] + - [[AI Risks/Technology concerns/Explainability]] + - Challenges in explaining the complex [[LDI]] strategies to stakeholders. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - [[LDI]] strategies that conflict with [[ESG]] investment principles or stakeholder expectations. + - [[Data Management/Risks/Data Integrity]] + - Risk of data tampering or manipulation affecting liability calculations. + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[Data Management/Risks/Data Leakage]] + - Exposure of sensitive financial and liability data. +- ### [[ESG Investment Strategy]] + - **Description**: Integrates environmental, social, and governance (ESG) factors into the investment process to align with the fund's sustainability goals. + - **Datasets**: + - [[Financial Services/Investment Management/Market Data/ESG Data/Company ESG Ratings]] + - [[Financial Services/Investment Management/Market Data/News Data/ESG Related News]] + - [[Financial Services/Investment Management/Client Data/Fund Beneficiaries/ESG Preferences]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/ESG Bonds]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Incorrect ESG scores due to inaccurate data or model errors. + - [[AI Risks/Data-level risk/Data bias]] + - Bias in ESG data leading to inaccurate or unfair scoring and investment decisions. + - [[AI Risks/Technology concerns/Explainability]] + - Lack of transparency in ESG scoring models and investment decisions. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - Misalignment between ESG investment strategies and the fund’s stated sustainability goals. + - [[Data Management/Risks/Data Integrity]] + - Risks related to the integrity of ESG data and the authenticity of sources. + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[Data Management/Risks/Data Leakage]] + - Unauthorized access to proprietary ESG models and sensitive ESG preferences of beneficiaries. +- ### [[Investment Performance Analysis]] + collapsed:: true + - **Description**: Analyzes the performance of the Investment against benchmarks and historical data to inform investment strategy adjustments. + - **Datasets**: + - [[Financial Services/Investment Management/Market Data/Indices/Benchmark Index Data]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Bond Prices]] + - [[Financial Services/Investment Management/Market Data/Indices/Investment Performance Data]] + - [[Financial Services/Investment Management/Client Data/Fund Performance/Monthly and Quarterly Returns]] + - **Applicable Policies**: + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Performance analysis inaccuracies due to incorrect benchmark data or model errors. + - [[AI Risks/Technology concerns/Explainability]] + - Difficulty in explaining complex performance analysis results and their implications. + - [[AI Risks/Bias and fairness]] in [[Performance Assessment]] + - Bias in performance models that favor certain metrics over others, potentially misleading stakeholders. + - [[Data Management/Risks/Data Integrity]] + - Integrity issues with performance data, such as tampering or inaccurate reporting. + - [[AI Risks/Privacy and Data Leakage/Privacy and Data Leakage]] + - [[Data Management/Risks/Data Leakage]] + - Exposure of sensitive performance data or benchmarking results. +- ### [[Risk Management and Stress Testing]] + collapsed:: true + - **Description**: Evaluates the fund's resilience to various economic scenarios by simulating market shocks and economic downturns. + - **Datasets**: + - [[Financial Services/Investment Management/Market Data/Economic Data/Macroeconomic Indicators]] + - [[Financial Services/Investment Management/Market Data/Economic Data/Scenario Data]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Stock Prices]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Historical Bond Prices]] + - [[Financial Services/Investment Management/Client Data/Fund Liabilities/Projected Liabilities]] + - [[Financial Services/Investment Management/Client Data/Fund Performance/Historical Performance]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Bias]] in [[Scenario Selection]] + - Bias in the selection of stress test scenarios, potentially overlooking certain risks. + - [[AI Risks/Technology concerns/Explainability]] + - Challenges in explaining complex stress testing models and their results to stakeholders. + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Incorrect stress test results due to flawed scenario data or model errors. + - [[AI Risks/Systemic/Systemic]] + - Model failure under extreme scenarios, leading to inadequate risk management. + - [[Data Management/Risks/Data Integrity]] + - Risks related to the integrity of stress test data and scenario inputs. + - [[AI Risks/Privacy Leakage]] + - [[Data Management/Risks/Data Leakage]] + - Breach of sensitive stress test results or risk management strategies. + - +- ### [[Beneficiary Analysis and Forecasting]] + collapsed:: true + - **Description**: Analyzes demographic data to forecast future contributions and liabilities, and supports planning for future payouts. + - **Datasets**: + - [[Financial Services/Investment Management/Client Data/Fund Beneficiaries/Demographics]] + - [[Financial Services/Investment Management/Client Data/Fund Beneficiaries/Contribution History]] + - [[Financial Services/Investment Management/Client Data/Fund Liabilities/Projected Liabilities]] + - [[Financial Services/Investment Management/Economic Data/Inflation Rates]] + - [[Financial Services/Investment Management/Market Data/Asset Prices/Projected Returns]] + - **Applicable Policies**: + collapsed:: true + - [[Policies/Data Governance/Data Classification]] + - [[Policies/Data Governance/Sensitivity Classification]] + - [[Policies/Data Governance/Usage Classification]] + - [[Policies/Data Governance/Data Access]] + - [[Policies/Data Governance/Role-Based Access Control]] + - [[Policies/Data Governance/Least Privilege Principle]] + - [[Policies/Data Governance/Data Retention]] + - [[Policies/Data Governance/Data Quality]] + - [[Policies/Data Governance/Data Accuracy Standards]] + - [[Policies/Data Governance/Completeness and Consistency Checks]] + - [[Policies/Data Governance/Data Provenance]] + - [[Policies/Data Governance/Data Lineage Tracking]] + - [[Policies/Data Governance/Metadata Management]] + - [[Policies/Data Governance/Data Privacy]] + - [[Policies/Data Governance/GDPR Compliance]] + - [[Policies/Data Governance/CCPA Compliance]] + - [[Policies/AI Governance/Model Development]] + - [[Policies/AI Governance/Feature Engineering Guidelines]] + - [[Policies/AI Governance/Data Preparation Standards]] + - [[Policies/AI Governance/Model Validation]] + - [[Policies/AI Governance/Bias Detection Policy]] + - [[Policies/AI Governance/Fairness and Transparency Policy]] + - [[Policies/AI Governance/Performance Metrics Threshold]] + - [[Policies/AI Governance/Model Monitoring]] + - [[Policies/AI Governance/Drift Detection]] + - [[Policies/AI Governance/Performance Monitoring]] + - [[Policies/AI Governance/AI Ethics]] + - [[Policies/AI Governance/Ethical AI Usage Guidelines]] + - [[Policies/AI Governance/Value Alignment Policy]] + - [[Policies/AI Governance/AI Risk Management]] + - #### AI Risks + - [[AI Risks/Untruthful Content/Factuality Errors]] + - Incorrect forecasts due to inaccurate or outdated demographic data. + - [[AI Risks/Bias]] in [[Demographic Analysis]] + - Bias in forecasting models that may lead to unfair projections for certain demographic groups. + - [[AI Risks/Technology concerns/Explainability]] + - Difficulty in explaining complex forecasting models and their projections to stakeholders. + - [[AI Risks/Performance & Robustness/Performance Degradation]] + - Underperformance of forecasting models, leading to incorrect planning. + - [[AI Risks/Ethical Concerns/Value Alignment Issues]] + - Forecasting strategies that do not align with ethical considerations, such as privacy concerns. + - [[Data Management/Risks/Data Integrity]] + - Risks related to the integrity of demographic data and projections. + - [[Data Management/Risks/Data Leakage]] + - [[AI Risks/Privacy Leakage/Private Training Data]] + - Exposure of sensitive beneficiary data or forecasting models. \ No newline at end of file diff --git a/pages/market data.md b/pages/market data.md new file mode 100644 index 0000000..918209a --- /dev/null +++ b/pages/market data.md @@ -0,0 +1,5 @@ +- Typically a [[data domain]], containing data about participants of a particular market. + - Examples + - [[Energy Market Data]] + - [[Financial Market Data]] + - [[...]] \ No newline at end of file